01
Backend engineering
Python services, FastAPI endpoints and database-backed applications built around clear contracts and maintainable architecture.
Backend Software Engineer / Pakistan · Working globally
I build reliable backend applications for modern digital products.
I am a Software Engineer specialising in backend application development, building reliable APIs, backend services and data-driven software systems—with applied AI capabilities where they create real value.
Python · FastAPI · PostgreSQL · API engineering · Applied AI
“
The foundation is software engineering.
AI is an additional capability.
Technical direction
A focused practice grounded in the fundamentals that make software useful, inspectable and dependable.
02
Data-intensive systems
Reliable data workflows that turn operational inputs into useful reporting, automation and decision support.
03
Applied AI systems
AI capabilities integrated into real software workflows, with structured outputs, retrieval and failure handling in mind.
Selected engineering work
Projects and experience presented as engineering context—not a collection of technology badges.
01 Featured project · research prototype
AgentFault-Lab
A local-first laboratory for reproducing and evaluating fault recovery behaviour in multi-step agent workflows.
View on GitHub$ agentfault benchmark --policy state_aware
fault injected → recovery path evaluated
✓ invariant checked regression recorded
Reproduce the failure.
Find the broken invariant.
Prove the recovery.
Problem
Agent failures can be hard to reproduce, inspect or compare across recovery policies.
Implementation
Deterministic faults, structured traces, invariant checks, SQLite persistence and a FastAPI interface.
Verified from repository
Python · FastAPI · SQLite · deterministic simulator · pytest · Docker · CI/CD
Read the architecture02
Startup / MVP engineering
AI automation SaaS MVP
Six-week accelerator sprint covering FastAPI development, MVP architecture, document ingestion, LLM routing and structured outputs. Presented as experience rather than a public product claim.
03
Data engineering / reporting
Reporting automation workflows
Python ETL and KPI reporting workflows using Pandas, SQLAlchemy and PostgreSQL, with data quality checks to make recurring reporting more reliable.
Professional experience
Roles across startup product engineering, data automation, applied AI and technical teaching.
2025 — present
MUSTER
Founding AI Engineer
Building within an early-stage AI-powered account management product for marketing agencies, contributing across backend implementation, applied AI workflows and product engineering.
2025
1337 Ventures
Founding Engineer / MVP Build
Worked through a six-week accelerator sprint to shape an AI automation SaaS MVP: FastAPI development, application architecture, document ingestion, LLM routing and structured outputs.
2024 — 2025
NIC Faisalabad
AI / Data Engineer
Developed Python ETL and reporting workflows using Pandas, SQLAlchemy and PostgreSQL, with data processing and quality checks supporting KPI reporting for portfolio companies.
2024 — 2025
Stanford Code in Place
Section Leader
Supported learners with Python fundamentals, debugging and problem-solving through structured teaching and technical guidance.
Capabilities
A practical toolkit for taking backend features from a clear problem to a reliable implementation.
Backend engineeringPython · FastAPI · REST APIs
Python · FastAPI · REST APIs
Backend architecture · Integrations
Databases & data engineeringPostgreSQL · SQLAlchemy · Pandas
PostgreSQL · SQLAlchemy · Pandas
ETL pipelines · Data processing
Applied AILLM applications · RAG
LLM applications · RAG
Document processing · Structured outputs
Engineering & deliveryTesting · Docker · CI/CD
Testing · Docker · CI/CD
Debugging · Documentation
How I approach engineering
The principles behind the code and the decisions around it.
01
Design around contracts
Good APIs make behavior explicit—for callers, maintainers and the next engineer joining the project.
02
Make failure visible
Retries, fallbacks and error states should be deliberate, observable and easy to reason about.
03
Ship useful complexity
The best implementation is not the most fashionable one. It is the one that solves the real problem and remains maintainable.
About
Useful systems,
carefully built.
I am a software engineer focused on backend application development, with experience across Python-based systems, APIs, data engineering and applied AI.
I enjoy solving practical engineering problems—from backend services and third-party integrations to data pipelines and AI-enabled workflows. My approach emphasises clear system design, reliable integrations, maintainable implementation, testing and documentation.
I am currently studying Software Engineering at the National University of Modern Languages (NUML), and I am interested in building robust software systems with teams that value engineering quality and practical execution.
GitHubSoftware Engineering · Sep 2022 — Jun 2026
Education & recognition
Foundations that
keep me learning.
EducationNational University of Modern Languages
Software Engineering · September 2022 — June 2026
TeachingStanford Code in Place
Section Leader · Python support, debugging and student guidance
Start a conversation
Let's build reliable
software.
For an engineering opportunity or a clearly scoped backend project, I would be glad to hear what you are working on.
I help software teams implement Python backend features, APIs and data workflows through clearly scoped engineering engagements.